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Exploring local service allocation in Community Networks

机译:探索社区网络中的本地服务分配

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Community Cloud computing is a new trend on cloud computing that aims to build service infrastructures upon Wireless Community Networks taking advantage of underused community physical resources. Service allocation protocols are a key design challenge that all cloud systems must properly address to optimize resource utilization. They are specially important when cloud services require a Quality of Service (QoS) and network stability or performance (delay, jitter, minimum bandwidth) cannot be guaranteed a-priory. This work presents a study that tries to understand how to address cloud service deployments in such scenario. In particular, we start proposing an allocation algorithm to find optimal solutions when there is a central authority that coordinates the process. These solutions optimize the communication cost in two ways: (1) minimizing the service overlay diameter and, (2) minimizing the coordination cost along the network. Based on the study of the algorithm and the experimental simulations, we study the variables that outcome optimal service allocations to the detriment of other solutions. We verify these findings using data mining techniques. Researchers can take advantage of the simulation results and our observations to design more reliable distributed algorithms able to dynamically self-adapt to network changes.
机译:社区云计算是云计算的一种新趋势,旨在利用未充分利用的社区物理资源在无线社区网络上构建服务基础架构。服务分配协议是关键的设计挑战,所有云系统必须正确解决这些挑战,以优化资源利用率。当云服务需要服务质量(QoS)且无法保证网络稳定性或性能(延迟,抖动,最小带宽)时,它们特别重要。这项工作提出了一项研究,试图了解如何解决这种情况下的云服务部署。特别是,我们开始提出一种分配算法,以在有协调流程的中央机构时找到最佳解决方案。这些解决方案通过两种方式来优化通信成本:(1)最小化服务覆盖范围的直径;(2)最小化沿网络的协调成本。基于算法的研究和实验仿真,我们研究了导致最优服务分配而不利于其他解决方案的变量。我们使用数据挖掘技术来验证这些发现。研究人员可以利用仿真结果和我们的观察结果,设计出更可靠的分布式算法,以动态地自适应网络变化。

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